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  2. Negative relationship - Wikipedia

    en.wikipedia.org/wiki/Negative_relationship

    Negative correlation can be seen geometrically when two normalized random vectors are viewed as points on a sphere, and the correlation between them is the cosine of the circular arc of separation of the points on a great circle of the sphere. [1] When this arc is more than a quarter-circle (θ > π/2), then the cosine is negative.

  3. Guess the Correlation - Wikipedia

    en.wikipedia.org/wiki/Guess_the_Correlation

    The game features both single and two-player modes and has a retro 8-bit design and sound effects. [ 1 ] [ 4 ] Collected guesses are used to better understand how humans perceive correlations in scatter plots by identifying features within scatter plots, such as outliers, that cause players to over or under estimate the true correlation.

  4. Spurious correlation of ratios - Wikipedia

    en.wikipedia.org/wiki/Spurious_correlation_of_ratios

    Form the proper fractions x/z and y/z for each triplet, and correlation will be found between these indices. The scatter plot above illustrates this example using 500 observations of x, y, and z. Variables x, y and z are drawn from normal distributions with means 10, 10, and 30, respectively, and standard deviations 1, 1, and 3 respectively, i.e.,

  5. Correlation - Wikipedia

    en.wikipedia.org/wiki/Correlation

    The correlation coefficient is +1 in the case of a perfect direct (increasing) linear relationship (correlation), −1 in the case of a perfect inverse (decreasing) linear relationship (anti-correlation), [5] and some value in the open interval (,) in all other cases, indicating the degree of linear dependence between the variables. As it ...

  6. Covariance and correlation - Wikipedia

    en.wikipedia.org/wiki/Covariance_and_correlation

    Notably, correlation is dimensionless while covariance is in units obtained by multiplying the units of the two variables. If Y always takes on the same values as X , we have the covariance of a variable with itself (i.e. σ X X {\displaystyle \sigma _{XX}} ), which is called the variance and is more commonly denoted as σ X 2 , {\displaystyle ...

  7. Polynomial regression - Wikipedia

    en.wikipedia.org/wiki/Polynomial_regression

    [3] [4] In the twentieth century, polynomial regression played an important role in the development of regression analysis, with a greater emphasis on issues of design and inference. [5] More recently, the use of polynomial models has been complemented by other methods, with non-polynomial models having advantages for some classes of problems.

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